The increasing emissions of greenhouse gases (GHG) and pollutants like particulate matter and nitrogen oxides (NOx) have led to environmental concerns. Hybrid and electric powertrains are being introduced as means to reduce pollutant emissions, especially at the local level. Additionally, the finite availability of fossil fuel sources, which are used to produce gasoline and diesel, highlights the need for alternative technical solutions. One approach to partly address these issues is lightweighting, which involves reducing the weight of vehicles to minimize their impact during the use phase. Mathematical models are employed to simulate the longitudinal dynamics of vehicles and estimate the energy required to accomplish driving missions. Appropriate metrics have been developed to quantify energy-saving effects that, in addition, can support the decision making, design, and development phase of future vehicles. To facilitate this process, it would be useful to build a database of ERV (Energy Reduction Value) and FRV (Fuel Reduction Value) figures derived through a unified procedure. Such a database would be useful in evaluating the effectiveness of vehicle lightweighting and its impact on energy consumption and pollutant emissions. The last phase of the analysis is the assessment of the overall reduction in the environmental impact of the vehicle throughout its life cycle by using the LCA (Life Cycle Assessment) approach. From this study, it was possible to conclude that lightweighting can be an appropriate solution to improve the energy efficiency of vehicles and that appropriate metrics, can support the development of new car models. The potential to integrate enhanced energy efficiency, lower emissions, and higher safety features into our everyday vehicles would represent a significant advancement in the automotive industry. There is a gap in the scientific literature on the effects of lightweighting on vehicle dynamics and energy usage which deserves to be investigated.

Nowadays, the topic of reducing vehicles’ energy consumption is very important. In particular, for electric vehicles, the reduction of energy consumption is necessary to remedy the most critical problems associated with this type of vehicle: the problem of the limited range of the electric traction, also associated with the long recharging times of the battery packs. To reduce use-phase impacts and energy consumptions of vehicles, it is useful to reduce the vehicle mass (lightweighting). The aim of this work is to analyze the parameters of a vehicle which influence the results of lightweighting, in order to provide guidelines for the creation of a vehicle model suitable for studying the effects of lightweighting. This study was carried out through two borderline case models, a compact car and an N1 vehicle, and simulating these through a consolidated vehicle simulation tool useful for consumption estimations. This study shows that the parameters that most influence the outcome of lightweighting are the rolling resistance, the battery pack characteristics, the aerodynamic coefficients, and the transmission efficiency, while the inertia contributions can be considered negligible. An analysis was also carried out with the variation of the driving cycle considered.

Today, reducing vehicle energy consumption is a crucial topic. For electric vehicles, reducing energy consumption is essential to address some of the most critical issues associated with this type of vehicle, such as the limited range of electric powertrains and the long battery recharging times. To lower the environmental impact during the vehicle’s use phase and reduce energy consumption, vehicle mass reduction (lightweighting) is an effective strategy. The objective of this work is to analyze the vehicle parameters that influence lightweighting outcomes on a real driving cycle, representative of the home-to-work travel in northern Italy. In particular, a previous work carried out on standard driving cycles is repeated in order to observe whether it is possible to draw the same conclusions regarding the variability in the lightweighting outcome. This study was conducted using two opposite vehicle models, a compact car and an N1 vehicle, simulated through a well-established vehicle simulation tool for energy consumption estimation. To conduct this analysis, several simulations with variable vehicle mass, and with different vehicle parameters, such as aerodynamics and rolling resistance, were performed to estimate energy consumption across a real-world driving cycle, acquired via GPS on board the vehicle during a home-to-work journey in northern Italy. This study reveals that even for the real driving cycle, as for the WLTC and US06 standards, the parameters that most influence the outcome of the lightening are the rolling resistance, the characteristics of the battery pack, the aerodynamic coefficients, and the efficiency of the transmission. Finally, the standard cycle that best fits with the real one considered in this study is the Artemis Urban Cycle.

Nowadays environmental sustainability is a hot topic, especially with regards to the transportation sector. In fact, political strategies are oriented to the transition towards the cleaner technologies to reduce polluting and climate-altering emissions. However, even fully electric vehicles are not characterized by zero global emissions, due to the production of electricity from sources that are not always renewable. Moreover, this type of vehicle is afflicted by the limited range provided by the battery pack and its long recharging time. So, it is useful to reduce the energy consumption through appropriate strategies, for example by means of the vehicle lightweighting. In this paper we focus on the battery pack lightweighting by considering different passive battery cooling systems as a replacement for the standard active one. The passive systems considered are air and PCM-based (Phase Change Material) cooling systems. In addition to the primary lightweighting given by the replacement of the cooling system, the secondary lightweighting obtained by reducing the capacity of the battery pack to return to the range of the starting reference vehicle has been also considered. Three tools were used for the study: VI-CarRealTime and another consolidate vehicle model to obtain the power demand on a standard driving cycle; and an ad-hoc battery system model, configurable according to the cooling system. The simulations showed that the air-cooled system leads to greater lightweighting, but it makes the battery cells work far from 20 °C (optimal operating temperature) and therefore it could lead to greater battery cell degradation and its field of application must be limited to vehicles operating in fleets, with predictable mission; this can be overcome by using an appropriate PCM-based cooling system, stearyl alcohol. Furthermore, using a PCM, glycerol, with a melting point close to the optimal operating temperature of the batteries, allows to reduce the cell degradation.

Today, reducing vehicle energy consumption is a crucial topic. For electric vehicles, reducing energy consumption is essential to address some of the most critical issues associated with this type of vehicle, such as the limited range of electric powertrains and the long battery recharging times. To lower the environmental impact during the vehicle’s use phase and reduce energy consumption, vehicle mass reduction (lightweighting) is an effective strategy. The objective of this work is to analyze the vehicle parameters that influence lightweighting outcomes on a real driving cycle, representative of the home-to-work travel in the northern Italy. In particular, a previous work carried out on standard driving cycles is repeated, in order to observe whether it is possible to draw the same conclusions regarding the variability of the lightweighting outcome. This study was conducted using two opposite vehicle models, a compact car and an N1 vehicle, simulated through a well-established vehicle simulation tool for energy consumption estimation. The study reveals that even for the real driving cycle, as for the WLTC and US06 standards, the parameters that most influence the outcome of the lightening are rolling resistance, the characteristics of the battery pack, the aerodynamic coefficients and the efficiency of the transmission. Finally, the standard cycle that best fits with the real one considered in this study is the Artemis Urban Cycle.

The automotive industry is moving toward cleaner and more sustainable solutions, with vehicle lightweighting emerging as a key strategy to reduce greenhouse gas and nitrogen oxides emissions. While the energy benefits of lightweighting are well documented, its influence on vehicle dynamics and active safety remains less explored. Focusing on a D-segment passenger car during double lane change manoeuvres, this study evaluates the effects of mass variations on pure lateral dynamics. A virtual vehicle model was developed within the VI-CarRealTime^® environment and calibrated to replicate the real vehicle behaviour measured during on-track testing. The model tuning process was enhanced by the installation of several measurement devices that provided experimental signals of both driver inputs and vehicle outputs, to perform realistic offline simulations. Finally, the use of a driving simulator integrating the tuned simulation model and Driver-In-the-Loop (DiL) allows for the investigation of various loading conditions. Since physical weight reduction was not feasible, additional mass was applied through ballasts to assess how increased weight alters the vehicle’s dynamic response compared to the unloaded condition. Meanwhile, lightweight configurations were evaluated solely in simulation across two distinct scenarios. Double Lane Change manoeuvres performed in the driving simulator highlighted differences in vehicle dynamics across mass configurations, although quantitative metrics were limited by the simulator feedback characteristics and driver variability. Despite these constraints, the simulator experiments offered qualitative insights consistent with theoretical expectations, confirming the sensitivity of vehicle handling and stability to mass distribution and total weight, and supporting the validity of the digital twin for future investigations.